Preliminary research IDs risk factors for hospitalization

Action Points

Note that this observational study of children with acute respiratory infection in the outpatient setting developed a risk scoring system, "STARWAVe," to help physicians to determine who should receive antibiotics.

A clinical decision-support tool developed from specific criteria associated with a young child's likelihood of being admitted to the hospital, may have the potential to decrease unnecessary antibiotic usage, according to preliminary data from a large prognostic study.

Using a child's symptoms as a guide, assigning a point for each symptom, this "coefficient-based clinical rule" was able to predict whether or not a child required hospitalization for their illness (area under the receiver-operating characteristic curve 0.81, 95% CI 0.76-0.85), reported Alastair D. Hay, MBChB, of the University of Bristol in England and colleagues.

Under this point system, children with a respiratory infection were identified as being at the highest, middle or lowest risk of hospitalization. The authors estimated that if antibiotic use was halved in the low risk group, remained constant in the high risk group and increased to 90% in the high risk group, this would lead to a 10% overall reduction in antibiotic prescriptions.

"The aim of our study was to develop a simple, usable prediction tool based on symptoms and signs to help [PCPs] and nurses identify children presenting in primary care at the lowest and highest risk of future complications and hospitalization, so that antibiotics can be targeted accordingly," said Hay in a statement.

Researchers examined data from 8,394 children ages 3 months to 16 years across 247 practices across England, who presented with an acute cough and respiratory tract infection. These patients were then followed for 30 days, and seven criteria independently associated with an increased risk of hospital admission were identified:

They then devised STARWAVe, a mnemonic device of symptoms where the child received a point for each symptom:

Short illness (≤3 days)

Temperature

Age (<24 months)

Recession

Wheeze

Asthma

Vomiting

Applying this tool to the sample, researchers were able to distinguish three distinct risk groups for future hospital admission associated with respiratory tract infections:

Children with 1 point or less: 0.3%, or 1 in 328 risk of hospital admission (67% of sample)

Children with 2-3 points: 1.5% or 1 in 68 risk (30% of sample)

Children with 4-7 points: 11.8%, or 1 in 8.5 risk (3% of sample)

The eventual goal of the tool would not be to supplant clinical judgment, but to enhance it, Hay said.

"We hope that our proposed clinical tool might eventually enable doctors to quickly and easily identify their lowest and highest risk patients, although more research will be needed to determine just how effective it is in clinical practice," he added. "Doctors and nurses should still advise parents about the symptoms and signs they should look out for, and when to seek medical help."

Median age of children in the sample was 3 years, 52% were boys and 78% were white. Median time to hospital admission was 2 days, but overall, about 1% of the sample (78 children) was actually admitted. Children who were admitted were more likely to have current asthma and more consultations for respiratory tract infections in the past year, with shorter illnesses before consultations and higher carer-reported illness severity scores.

Based on the discharge diagnoses of hospitalized children, researchers determined that the probability of bacterial infection was 0.9% in the low-risk group, 0.38% in the middle risk group and 3.92% in the high risk group. Yet, 33% of the low risk group, 44% of the middle risk group and 67% of the high risk group actually received antibiotics.

An accompanying editorial by Christopher C. Winchester, DPhil, of Oxford PharmaGenesis (a health consultancy firm in the U.K.), and colleagues, noted limitations to the study -- namely that validation of the model was only feasible via bootstrapping, and was limited by a low rate of hospital admission and lack of statistical power. But they added that it potentially could reduce antibiotic prescriptions, in combination with other tests.

"STARWAVe offers primary care clinicians an evidence-based practical tool to help guide antibiotic prescription decisions and, though shared decision-making, has the potential to reduce antibiotic prescription based on prognostic uncertainty or non-medical grounds," Winchester and colleagues wrote. "Combining this tool with point-of-care C-reactive protein testing, or to triage for CRP testing, might help to target antibiotic use further."

Accessibility Statement

At MedPage Today, we are committed to ensuring that individuals with disabilities can access all of the content offered by MedPage Today through our website and other properties. If you are having trouble accessing www.medpagetoday.com, MedPageToday's mobile apps, please email legal@ziffdavis.com for assistance. Please put "ADA Inquiry" in the subject line of your email.